Hi,
I have the following sample dataset
ID | Purchase Date | Age | Sales |
3621901 | 04/01/2010 | 21 | 990 |
6271017 | 04/01/2010 | 29 | 642 |
3914676 | 02/01/2010 | 26 | 955 |
3888167 | 04/01/2010 | 32 | 834 |
3888167 | 04/01/2010 | 30 | 616 |
3888167 | 04/01/2010 | 38 | 657 |
3289156 | 04/01/2010 | 33 | 322 |
3621901 | 30/11/2011 | 27 | 855 |
6271017 | 31/05/2012 | 40 | 381 |
3914676 | 11/06/2012 | 29 | 915 |
3888167 | 11/06/2012 | 40 | 972 |
3015141 | 28/05/2012 | 26 | 755 |
4518247 | 28/05/2012 | 31 | 415 |
4518247 | 13/06/2012 | 30 | 652 |
having 3 years of data for different customers & as seen the customers ids may repeat over 2 different point in time.How is it best possible to run a predictive model given there are different point of time involved with same customer ids?
Would be great if you can advice.